Reliable and efficient storage of data and, in particular, data used by enterprises is becoming increasingly important. Various data duplication, backup and/or data mirroring techniques are used by enterprise data storage systems. Typically, the data is distributed over several data servers, so that a crash of one server or loss of the connection to that server does not affect the data integrity.
Various approaches exist that enable resources such as data centers and Internet-Protocol (IP)-based networks to scale as the needs of the various users and applications increase. In some cases, this requires the purchase of large, expensive hardware that typically provides more capacity than is immediately necessary. For a large number of resources to be used, this can provide a significant expenditure and overhead, which can be undesirable in many instances and likely requires manual calibration/tuning based on hardcoded Quality of Storage (QoSt) concepts.
It is desired to have the level or redundancy, the level of reliability and the level of data availability as a single service, so a user can have choices and can select certain guarantees of data availability and of quality of data storage.